METHODS: We studied 130 consecutive dyads of family caregivers and patients. Factor analysis of the 22-item ZBI revealed four factors of burden. We compared WaP (factor 4) with the other three factors, personal strain, and role strain via: internal consistency; inter-factor correlation; item-to-total ratio across Clinical Dementia Rating (CDR) stages; predictors of burden; and interaction effect on total ZBI score using two-way analysis of variance.
RESULTS: WaP correlated poorly with the other factors (r = 0.05-0.21). It had the highest internal consistency (Cronbach's α = 0.92) among the factors. Unlike other factors, WaP was highly endorsed in mild cognitive impairment and did not increase linearly with disease severity, peaking at CDR 1. Multiple regression revealed younger caregiver age as the major predictor of WaP, compared with behavioral and functional problems for other factors. There was a significant interaction between WaP and psychological strain (p = 0.025).
CONCLUSION: Our results corroborate earlier studies that WaP is a distinct burden dimension not correspondent with traditional ZBI domains. WaP is germane to many Asian societies where obligation values to care for family members are strongly influential. Further studies are needed to better delineate the construct of WaP.
METHODS: Data for 91 countries were obtained from United Nations agencies. The response variable was life expectancy, and the determinant factors were demographic events (total fertility rate and adolescent fertility rate), socioeconomic status (mean years of schooling and gross national income per capita), and health factors (physician density and human immunodeficiency virus [HIV] prevalence rate). Path analysis was used to determine the direct, indirect, and total effects of these factors on life expectancy.
RESULTS: All determinant factors were significantly correlated with life expectancy. Mean years of schooling, total fertility rate, and HIV prevalence rate had significant direct and indirect effects on life expectancy. The total effect of higher physician density was to increase life expectancy.
CONCLUSIONS: We identified several direct and indirect pathways that predict life expectancy. The findings suggest that policies should concentrate on improving reproductive decisions, increasing education, and reducing HIV transmission. In addition, special attention should be paid to the emerging need to increase life expectancy by increasing physician density.